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Blocking sparse method for image denoising

delete2021-03-20
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PRE
AI
J
Jianjun Yuan *
J
Jiao He
DOI:10.1007/s10044-021-00974-0delete
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摘要

摘要

En 中文
In recent years, compressive sensing has been one promising technique for denoising images. This paper presents a new denoising model based on blocking sparsity. First, an image is blocked. Second, the split-Bregman method is used to solve for each block image. Finally, all denoised block images are combined into one image. Compared with the latest HTV, GHNS, FastATV, CSR and BM3D models, experimental results demonstrate that the proposed method is efficient, and has better denoising capability.
Keyword:
Image denoising
Split-Bregman method
Block image
Compressive sensing
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期刊

Pattern Analysis and Applications 封面图
Pattern Analysis and Applications
IF:
2
论文数:
2.0K
被引数:
1.9K

机构

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southwest university - china
学者数:
2.6W
论文数: 1.9W
被引数: 21
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